Socially-Aware Energy-Efficient Task Partial Offloading in MEC Networks With D2D Collaboration
Hao Long, Chen Guang Xu, Guangyuan Zheng, Yun Sheng · IEEE Transactions on Green Communications and Networking · 2022
The future wireless network will face demands of massive connectivity and intensive computation with the increase of mobile devices. Mobile edge computing (MEC) and Device-to-Device (D2D) have emerged as promising technologies to address the above challenges, and implementing social relationships in D2D-MEC networks can improve the reliability of D2D links. Exploiting these benefits, we investigate the energy-efficient task offloading problem in socially-aware D2D-assisted MEC networks, where the user devices can offload tasks to the nearby device or further forward to the MEC server based on social relationships. Specifically, we design a task partial offloading scheme of joint D2D connection selection, transmit power control and task allocation, to maximize the long-term network utility with considering dynamic system status and random task arrival. First, the social relationship among users is quantified into a social trust matrix. As the formulated socially-aware energy-efficient problem is a long-term stochastic optimization problem that is directly intractable, we thus employ the Lyapunov optimization to transform it into a series of short-term problems, each of which can be solved by the Karush-Kuhn-Tucker method and a pricing-based matching algorithm. Finally, we verify the performance optimality and the long-term network stability through numerical simulations as well as theoretical analysis.